Proposing a load balancing method based on Cuckoo Optimization Algorithm for energy management in cloud computing infrastructures

With rapid increasing demand of cloud computing technology, energy efficiency has become highly important in cloud computing infrastructures. Cloud computing concept offers low cost and high level of availability. However, it still has some challenging problems, such as resource management and power consumption. In this concept, reducing energy consumption and maximize resource utilization, became a primary concerns of many resource management methods. In this paper, we presented an approach based on Cuckoo Optimization Algorithm (COA) to detect over-utilized hosts. Following that, we employed The Minimum Migration Time (MMT) policy to migrate Virtual Machines (VMs) from the over-utilized hosts to the other hosts. Meanwhile, the migration process should not make any more over-utilized host. Finally, we considered all the hosts, except the over-utilized ones, as the underutilized hosts. At that point, we tried to migrate all the VMs which been allocated to the underutilized hosts to the other hosts and switch them to the sleep mode. The Simulation results which generated by Cloudsim simulator, demonstrate that the proposed approach has lowest energy consumption compared to the other famous algorithms like MAD-MMT(Median Absolute Deviation- Minimum Migration Time), IQR-MMT(Interquartile Range- Minimum Migration Time), Bee-MMT(Bee colony algorithm- Minimum Migration Time), LR-MMT(local Regression-Minimum Migration Time) and non-power aware.